New model predicts how mosquitoes will fly
Their flight patterns change in response to different sensory cues, a new study finds. The work could lead to more effective traps and mosquito control strategies.
Their flight patterns change in response to different sensory cues, a new study finds. The work could lead to more effective traps and mosquito control strategies.
Researchers at MIT, Mass General Brigham, and Harvard Medical School developed a deep-learning model to forecast a patient’s heart failure prognosis up to a year in advance.
Professor Jesse Thaler describes a vision for a two-way bridge between artificial intelligence and the mathematical and physical sciences — one that promises to advance both.
Over 2,500 — including coaches and players from Team USA, the NBA, WNBA, and more — attended MIT’s industry-leading event, now in its 20th year.
A new approach could help users know whether to trust a model’s predictions in safety-critical applications like health care and autonomous driving.
By leveraging idle computing time, researchers can double the speed of model training while preserving accuracy.
By enabling two chips to authenticate each other using a shared fingerprint, this technique can improve privacy and energy efficiency.
Research from the MIT Center for Constructive Communication finds leading AI models perform worse for users with lower English proficiency, less formal education, and non-US origins.
A new method developed at MIT could root out vulnerabilities and improve LLM safety and performance.
MIT Sports Lab researchers are applying AI technologies to help figure skaters improve. They also have thoughts on whether five-rotation jumps are humanly possible.
Removing just a tiny fraction of the crowdsourced data that informs online ranking platforms can significantly change the results.
Munip Utama applies knowledge from the MITx MicroMasters Program in Data, Economics, and Design of Policy to his efforts supporting students in Indonesia.
Founded by two MIT alumni, Samsara’s platform gives companies a central hub to learn from their workers, equipment, and other infrastructure.
CSAIL researchers find even “untrainable” neural nets can learn effectively when guided by another network’s built-in biases using their guidance method.
MIT-IBM Watson AI Lab researchers developed an expressive architecture that provides better state tracking and sequential reasoning in LLMs over long texts.